| Fast Adaptation With Linearized Neural Networks | 0 | 0.34 | 2021 |
| Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data | 0 | 0.34 | 2021 |
| Deep Gaussian Processes for Multi-fidelity Modeling. | 0 | 0.34 | 2019 |
| Variational Information Distillation For Knowledge Transfer | 12 | 0.79 | 2019 |
| Leveraging Crowdsourcing Data for Deep Active Learning An Application: Learning Intents in Alexa. | 2 | 0.36 | 2018 |
| Deep Gaussian Processes with Convolutional Kernels. | 4 | 0.46 | 2018 |
| DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self. | 6 | 0.46 | 2018 |
| Transferring Knowledge across Learning Processes. | 5 | 0.39 | 2018 |
| Preferential Bayesian Optimization. | 0 | 0.34 | 2017 |
| Online Constrained Model-Based Reinforcement Learning | 2 | 0.36 | 2017 |
| Manifold Alignment Determination: finding correspondences across different data views. | 0 | 0.34 | 2017 |
| Probabilistic consolidation of grasp experience | 2 | 0.45 | 2016 |
| Recurrent Gaussian Processes | 0 | 0.34 | 2016 |
| A Bioinspired Approach to Vision. | 0 | 0.34 | 2016 |
| Variational Inference for Latent Variables and Uncertain Inputs in Gaussian Processes. | 0 | 0.34 | 2016 |
| iCub Visual Memory Inspector: Visualising the iCub's Thoughts. | 1 | 0.35 | 2016 |
| Multi-View Learning As A Nonparametric Nonlinear Inter-Battery Factor Analysis | 1 | 0.63 | 2016 |
| Variational Auto-encoded Deep Gaussian Processes | 0 | 0.34 | 2016 |
| Variational Auto-encoded Deep Gaussian Processes | 21 | 0.78 | 2015 |
| Extending a Hippocampal Model for Navigation Around a Maze Generated from Real-World Data. | 0 | 0.34 | 2015 |
| Semi-described and semi-supervised learning with Gaussian processes | 4 | 0.43 | 2015 |
| Recurrent Gaussian Processes | 0 | 0.34 | 2015 |
| A Top-Down Approach for a Synthetic Autobiographical Memory System | 3 | 0.44 | 2015 |
| Active learning for sparse bayesian multilabel classification | 26 | 0.83 | 2014 |
| Variational Inference for Uncertainty on the Inputs of Gaussian Process Models. | 6 | 0.63 | 2014 |
| Factorized Topic Models | 2 | 0.39 | 2013 |
| Manifold Relevance Determination | 13 | 1.22 | 2012 |
| Deep Gaussian Processes | 10 | 3.11 | 2012 |
| Variational Gaussian Process Dynamical Systems | 31 | 1.88 | 2011 |
